Each new plastic injection molding project has three inherent goals: performance for the customer; production efficiency for the manufacturer; and, reliability for the end user.
These goals are reasonable. The challenge lies in accomplishing all three within a desired timeframe and budget.
To do so, injection molding plastics engineers turn to Design of Experiments (DOE) to identify flaws during the process design phase that might otherwise derail project success.
What is Design of Experiments?
Generally speaking, DOE is one facet of scientific molding, a highly precise injection molding practice that improves end results and ROI for complex plastic parts and products. Specifically, DOE is a branch of applied statistics that uses input and output variables in controlled tests to determine certain values, such as part failure probability.
For engineers specially trained in scientific molding, a DOE matrix is key in decision-making since it reflects the sum and substance of the entire DOE process. DOE gathers statistical evidence through multiple measurements and balances them with external influences to run analysis and construct a mathematical model, as illustrated here:
Sample DOE graph
However, this deeper learning isn't math for math's sake. DOE allows engineers to accurately retrace steps, resolve any contradictions, and determine next steps — either recommended changes or further required testing.
Performance, Production Efficiency, and Reliability
DOE gives custom injection molders the ability to find the ideal process window, and better understand the result of having and maintaining it. The mathematical accuracy with which DOE displays the relationship between values and ideal outcomes is fundamental to scientific molding on the whole, and also to three key injection molding project goals:
Product and/or process design sensitivities and potential changes are revealed when DOE evaluates factors sometimes overlooked by product engineers — such as materials and injection molding settings (injection speed, melt temperature, cooling time, etc.).
The thorough process raises questions about their influence on design and fulfillment of project specs. As a result, corrective adjustments to input values or other standards can be made to ensure expected performance.
Through DOE, poor design is averted prior to manufacture since process outcome is verified. It also can prevent faulty plastic part designs from inadvertently reaching the production floor, as testing can reveal which manufacturing changes need to be made to correct missteps. This allows manufacturers to optimize their time and resources at every production step.
DOE is versatile and can be applied to gather data about the ability of plastic parts to withstand any number of environmental conditions. This granular knowledge reveals design flaws and potential failure risks, providing ample time for modifications that translate to better, more reliable products going to market.
DOE is a scientific molding imperative and a mathematically precise way to ensure best outcomes of plastic injection molding projects for customers, manufacturers, and end users. Learn more in our white paper, An OEM's Guide to Scientific Molding. Click the button below to download your free copy.